Overview

Dataset statistics

Number of variables8
Number of observations694500
Missing cells2637265
Missing cells (%)47.5%
Duplicate rows180
Duplicate rows (%)< 0.1%
Total size in memory42.4 MiB
Average record size in memory64.0 B

Variable types

Numeric8

Alerts

Dataset has 180 (< 0.1%) duplicate rowsDuplicates
reflectivity is highly overall correlated with total_powerHigh correlation
total_power is highly overall correlated with reflectivityHigh correlation
reflectivity has 669781 (96.4%) missing valuesMissing
total_power has 591788 (85.2%) missing valuesMissing
velocity has 690519 (99.4%) missing valuesMissing
spectrum_width has 685177 (98.7%) missing valuesMissing

Reproduction

Analysis started2024-04-18 09:32:34.661037
Analysis finished2024-04-18 09:32:41.600306
Duration6.94 seconds
Software versionydata-profiling vv4.7.0
Download configurationconfig.json

Variables

longitude
Real number (ℝ)

Distinct628805
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.696635
Minimum7.9691935
Maximum13.349942
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2024-04-18T16:32:41.650889image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum7.9691935
5-th percentile8.7690589
Q110.026549
median10.681468
Q311.388629
95-th percentile12.592085
Maximum13.349942
Range5.3807485
Interquartile range (IQR)1.3620805

Descriptive statistics

Standard deviation1.0907156
Coefficient of variation (CV)0.1019681
Kurtosis-0.2611624
Mean10.696635
Median Absolute Deviation (MAD)0.681308
Skewness-0.031300086
Sum7428812.9
Variance1.1896604
MonotonicityNot monotonic
2024-04-18T16:32:41.722868image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.65961 1390
 
0.2%
10.659763 11
 
< 0.1%
10.659426 8
 
< 0.1%
10.6580925 8
 
< 0.1%
10.659678 7
 
< 0.1%
10.659652 7
 
< 0.1%
10.6553545 6
 
< 0.1%
10.680629 6
 
< 0.1%
10.659812 6
 
< 0.1%
10.657205 6
 
< 0.1%
Other values (628795) 693045
99.8%
ValueCountFrequency (%)
7.9691935 1
< 0.1%
7.969471 1
< 0.1%
7.9695344 1
< 0.1%
7.9705777 1
< 0.1%
7.9706645 1
< 0.1%
7.9719095 1
< 0.1%
7.9722543 1
< 0.1%
7.972479 1
< 0.1%
7.972832 1
< 0.1%
7.972857 1
< 0.1%
ValueCountFrequency (%)
13.349942 1
< 0.1%
13.349633 1
< 0.1%
13.349595 1
< 0.1%
13.348596 1
< 0.1%
13.348468 1
< 0.1%
13.3476095 1
< 0.1%
13.347404 1
< 0.1%
13.347104 1
< 0.1%
13.346597 1
< 0.1%
13.346461 1
< 0.1%

latitude
Real number (ℝ)

Distinct388402
Distinct (%)55.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean106.75614
Minimum103.99065
Maximum109.46598
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2024-04-18T16:32:41.790161image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum103.99065
5-th percentile104.76983
Q1106.05684
median106.75115
Q3107.47215
95-th percentile108.69708
Maximum109.46598
Range5.475326
Interquartile range (IQR)1.4153063

Descriptive statistics

Standard deviation1.122769
Coefficient of variation (CV)0.010517137
Kurtosis-0.30164581
Mean106.75614
Median Absolute Deviation (MAD)0.7081075
Skewness-0.04248564
Sum74142142
Variance1.2606102
MonotonicityNot monotonic
2024-04-18T16:32:41.862315image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
106.728325 1389
 
0.2%
106.73351 20
 
< 0.1%
106.73381 19
 
< 0.1%
106.732925 18
 
< 0.1%
106.72284 18
 
< 0.1%
106.72406 17
 
< 0.1%
106.7338 17
 
< 0.1%
106.73006 16
 
< 0.1%
106.72719 16
 
< 0.1%
106.72699 16
 
< 0.1%
Other values (388392) 692954
99.8%
ValueCountFrequency (%)
103.990654 1
< 0.1%
103.99074 1
< 0.1%
103.99149 1
< 0.1%
103.991646 1
< 0.1%
103.993126 1
< 0.1%
103.993324 1
< 0.1%
103.99335 1
< 0.1%
103.99342 1
< 0.1%
103.99409 1
< 0.1%
103.99422 1
< 0.1%
ValueCountFrequency (%)
109.46598 1
< 0.1%
109.46589 1
< 0.1%
109.46525 1
< 0.1%
109.46504 1
< 0.1%
109.46374 1
< 0.1%
109.46367 1
< 0.1%
109.46317 1
< 0.1%
109.46315 1
< 0.1%
109.462395 1
< 0.1%
109.46235 1
< 0.1%

altitude
Real number (ℝ)

Distinct23167
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7281.3861
Minimum10
Maximum24684
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2024-04-18T16:32:41.933878image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile390
Q12482
median5940
Q310989
95-th percentile18700
Maximum24684
Range24674
Interquartile range (IQR)8507

Descriptive statistics

Standard deviation5807.8991
Coefficient of variation (CV)0.79763647
Kurtosis-0.056046087
Mean7281.3861
Median Absolute Deviation (MAD)3961
Skewness0.84620343
Sum5.0569227 × 109
Variance33731692
MonotonicityNot monotonic
2024-04-18T16:32:42.006522image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10 1389
 
0.2%
26 389
 
0.1%
15 256
 
< 0.1%
48 243
 
< 0.1%
43 227
 
< 0.1%
36 206
 
< 0.1%
86 203
 
< 0.1%
87 201
 
< 0.1%
125 185
 
< 0.1%
60 183
 
< 0.1%
Other values (23157) 691018
99.5%
ValueCountFrequency (%)
10 1389
0.2%
13 1
 
< 0.1%
14 18
 
< 0.1%
15 256
 
< 0.1%
16 33
 
< 0.1%
17 2
 
< 0.1%
18 7
 
< 0.1%
19 7
 
< 0.1%
20 69
 
< 0.1%
21 177
 
< 0.1%
ValueCountFrequency (%)
24684 1
 
< 0.1%
24670 1
 
< 0.1%
24641 2
< 0.1%
24627 3
< 0.1%
24624 1
 
< 0.1%
24612 1
 
< 0.1%
24609 1
 
< 0.1%
24598 3
< 0.1%
24584 1
 
< 0.1%
24581 2
< 0.1%

reflectivity
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct5382
Distinct (%)21.8%
Missing669781
Missing (%)96.4%
Infinite0
Infinite (%)0.0%
Mean1.5609632
Minimum-35.57
Maximum57.89
Zeros7
Zeros (%)< 0.1%
Negative13015
Negative (%)1.9%
Memory size5.3 MiB
2024-04-18T16:32:42.080360image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-35.57
5-th percentile-15.75
Q1-8.86
median-1.15
Q311.65
95-th percentile24.991
Maximum57.89
Range93.46
Interquartile range (IQR)20.51

Descriptive statistics

Standard deviation13.135602
Coefficient of variation (CV)8.4150616
Kurtosis-0.42415256
Mean1.5609632
Median Absolute Deviation (MAD)9.4
Skewness0.51791294
Sum38585.45
Variance172.54403
MonotonicityNot monotonic
2024-04-18T16:32:42.155875image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-7.85 23
 
< 0.1%
-6.51 22
 
< 0.1%
-8.04 20
 
< 0.1%
-10.75 19
 
< 0.1%
-9.8 19
 
< 0.1%
-6.22 18
 
< 0.1%
-9.19 17
 
< 0.1%
-5.51 17
 
< 0.1%
-7.99 17
 
< 0.1%
-10.5 17
 
< 0.1%
Other values (5372) 24530
 
3.5%
(Missing) 669781
96.4%
ValueCountFrequency (%)
-35.57 1
< 0.1%
-34.47 1
< 0.1%
-33.63 1
< 0.1%
-32.73 1
< 0.1%
-32.18 1
< 0.1%
-31.36 1
< 0.1%
-31.23 1
< 0.1%
-31.19 1
< 0.1%
-31.09 1
< 0.1%
-30.84 1
< 0.1%
ValueCountFrequency (%)
57.89 1
< 0.1%
55.61 1
< 0.1%
54.36 1
< 0.1%
52.3 1
< 0.1%
51.79 1
< 0.1%
50.37 1
< 0.1%
50.24 1
< 0.1%
48.15 1
< 0.1%
47.7 1
< 0.1%
46.94 1
< 0.1%

total_power
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct7857
Distinct (%)7.6%
Missing591788
Missing (%)85.2%
Infinite0
Infinite (%)0.0%
Mean8.6153701
Minimum-25.62
Maximum77.68
Zeros30
Zeros (%)< 0.1%
Negative33295
Negative (%)4.8%
Memory size5.3 MiB
2024-04-18T16:32:42.236561image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-25.62
5-th percentile-10.82
Q1-2.68
median6.77
Q316.83
95-th percentile37.26
Maximum77.68
Range103.3
Interquartile range (IQR)19.51

Descriptive statistics

Standard deviation14.847889
Coefficient of variation (CV)1.7234186
Kurtosis1.1415539
Mean8.6153701
Median Absolute Deviation (MAD)9.69
Skewness0.96230355
Sum884901.89
Variance220.45981
MonotonicityNot monotonic
2024-04-18T16:32:42.311300image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17.11 102
 
< 0.1%
17.13 99
 
< 0.1%
17.1 91
 
< 0.1%
17.12 88
 
< 0.1%
17.07 80
 
< 0.1%
17.09 75
 
< 0.1%
17.08 74
 
< 0.1%
17.05 70
 
< 0.1%
17.04 70
 
< 0.1%
17.14 70
 
< 0.1%
Other values (7847) 101893
 
14.7%
(Missing) 591788
85.2%
ValueCountFrequency (%)
-25.62 1
< 0.1%
-24.73 1
< 0.1%
-23.81 1
< 0.1%
-23.41 1
< 0.1%
-23.26 1
< 0.1%
-22.44 1
< 0.1%
-22.16 1
< 0.1%
-21.37 1
< 0.1%
-21.36 1
< 0.1%
-20.99 1
< 0.1%
ValueCountFrequency (%)
77.68 1
< 0.1%
76.35 1
< 0.1%
74.9 1
< 0.1%
74.67 1
< 0.1%
74.16 1
< 0.1%
74.13 1
< 0.1%
73.04 1
< 0.1%
72.81 1
< 0.1%
72.38 1
< 0.1%
72.29 1
< 0.1%

velocity
Real number (ℝ)

MISSING 

Distinct786
Distinct (%)19.7%
Missing690519
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean-0.30993469
Minimum-4.02
Maximum4.02
Zeros2
Zeros (%)< 0.1%
Negative2285
Negative (%)0.3%
Memory size5.3 MiB
2024-04-18T16:32:42.382042image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum-4.02
5-th percentile-3.82
Q1-2.62
median-0.89
Q32.15
95-th percentile3.81
Maximum4.02
Range8.04
Interquartile range (IQR)4.77

Descriptive statistics

Standard deviation2.6060645
Coefficient of variation (CV)-8.4084311
Kurtosis-1.3590743
Mean-0.30993469
Median Absolute Deviation (MAD)2.24
Skewness0.24840312
Sum-1233.85
Variance6.7915721
MonotonicityNot monotonic
2024-04-18T16:32:42.456834image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-3.77 19
 
< 0.1%
-3.83 15
 
< 0.1%
-3.85 15
 
< 0.1%
-3.23 15
 
< 0.1%
-2.17 14
 
< 0.1%
3.99 14
 
< 0.1%
-3.84 14
 
< 0.1%
-3.74 13
 
< 0.1%
-3.76 13
 
< 0.1%
-3.82 13
 
< 0.1%
Other values (776) 3836
 
0.6%
(Missing) 690519
99.4%
ValueCountFrequency (%)
-4.02 1
 
< 0.1%
-4.01 7
< 0.1%
-4 12
< 0.1%
-3.99 10
< 0.1%
-3.98 10
< 0.1%
-3.97 10
< 0.1%
-3.96 11
< 0.1%
-3.95 10
< 0.1%
-3.94 6
< 0.1%
-3.93 9
< 0.1%
ValueCountFrequency (%)
4.02 4
 
< 0.1%
4.01 11
< 0.1%
4 10
< 0.1%
3.99 14
< 0.1%
3.98 9
< 0.1%
3.97 9
< 0.1%
3.96 9
< 0.1%
3.95 13
< 0.1%
3.94 12
< 0.1%
3.93 9
< 0.1%

spectrum_width
Real number (ℝ)

MISSING 

Distinct227
Distinct (%)2.4%
Missing685177
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean0.98428081
Minimum0.01
Maximum2.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2024-04-18T16:32:42.531822image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum0.01
5-th percentile0.29
Q10.74
median0.99
Q31.23
95-th percentile1.65
Maximum2.52
Range2.51
Interquartile range (IQR)0.49

Descriptive statistics

Standard deviation0.39548235
Coefficient of variation (CV)0.4017983
Kurtosis0.1303397
Mean0.98428081
Median Absolute Deviation (MAD)0.24
Skewness0.046976429
Sum9176.45
Variance0.15640629
MonotonicityNot monotonic
2024-04-18T16:32:42.674059image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.97 125
 
< 0.1%
1.07 121
 
< 0.1%
0.96 118
 
< 0.1%
0.95 117
 
< 0.1%
0.99 115
 
< 0.1%
1.02 114
 
< 0.1%
1.03 114
 
< 0.1%
0.93 113
 
< 0.1%
1.09 110
 
< 0.1%
0.91 109
 
< 0.1%
Other values (217) 8167
 
1.2%
(Missing) 685177
98.7%
ValueCountFrequency (%)
0.01 96
< 0.1%
0.02 1
 
< 0.1%
0.04 4
 
< 0.1%
0.05 3
 
< 0.1%
0.06 4
 
< 0.1%
0.07 7
 
< 0.1%
0.08 5
 
< 0.1%
0.09 5
 
< 0.1%
0.1 5
 
< 0.1%
0.11 4
 
< 0.1%
ValueCountFrequency (%)
2.52 1
 
< 0.1%
2.43 1
 
< 0.1%
2.39 1
 
< 0.1%
2.37 1
 
< 0.1%
2.36 3
< 0.1%
2.3 1
 
< 0.1%
2.29 1
 
< 0.1%
2.23 2
< 0.1%
2.22 1
 
< 0.1%
2.2 2
< 0.1%

time
Real number (ℝ)

Distinct159
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87.973362
Minimum1
Maximum171
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.3 MiB
2024-04-18T16:32:42.741627image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q148
median91
Q3132
95-th percentile163
Maximum171
Range170
Interquartile range (IQR)84

Descriptive statistics

Standard deviation49.782457
Coefficient of variation (CV)0.56588103
Kurtosis-1.1833595
Mean87.973362
Median Absolute Deviation (MAD)42
Skewness-0.075074601
Sum61097500
Variance2478.293
MonotonicityNot monotonic
2024-04-18T16:32:42.819383image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
93 5500
 
0.8%
166 5500
 
0.8%
79 5500
 
0.8%
46 5000
 
0.7%
133 5000
 
0.7%
64 5000
 
0.7%
4 5000
 
0.7%
101 5000
 
0.7%
151 5000
 
0.7%
159 5000
 
0.7%
Other values (149) 643000
92.6%
ValueCountFrequency (%)
1 3500
0.5%
2 4500
0.6%
3 4500
0.6%
4 5000
0.7%
5 4500
0.6%
6 4000
0.6%
7 4000
0.6%
8 5000
0.7%
9 4000
0.6%
10 4500
0.6%
ValueCountFrequency (%)
171 4000
0.6%
170 4000
0.6%
169 4500
0.6%
168 4500
0.6%
167 4000
0.6%
166 5500
0.8%
165 4500
0.6%
164 3500
0.5%
163 4000
0.6%
162 5000
0.7%

Interactions

2024-04-18T16:32:40.196697image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.307176image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.895257image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.454614image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.016704image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.520529image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.188143image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.608013image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.277217image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.394134image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.969867image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.559350image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.068662image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.577763image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.242505image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.656451image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.365261image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.495117image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.056845image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.661458image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.120695image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.638080image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.292190image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.704544image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.416510image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.548788image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.113271image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.717970image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.169929image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.688933image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.348093image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.888689image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.478214image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.611746image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.171289image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.773647image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.219976image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.743726image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.397695image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.937063image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.527645image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.668209image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.227740image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.824487image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.266245image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.794018image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.446311image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.989389image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.586775image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.724953image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.285039image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.879881image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.408335image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.852874image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.502713image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.042115image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.662675image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:36.813372image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.364524image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:37.960393image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.459792image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:38.911244image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:39.553353image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
2024-04-18T16:32:40.093558image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/

Correlations

2024-04-18T16:32:42.873045image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
altitudelatitudelongitudereflectivityspectrum_widthtimetotal_powervelocity
altitude1.000-0.003-0.0160.322-0.0610.456-0.289-0.066
latitude-0.0031.000-0.0370.1950.017-0.1530.004-0.111
longitude-0.016-0.0371.000-0.2190.225-0.1540.0190.057
reflectivity0.3220.195-0.2191.0000.142-0.4680.889-0.065
spectrum_width-0.0610.0170.2250.1421.000-0.1170.365-0.009
time0.456-0.153-0.154-0.468-0.1171.000-0.2800.078
total_power-0.2890.0040.0190.8890.365-0.2801.000-0.024
velocity-0.066-0.1110.057-0.065-0.0090.078-0.0241.000

Missing values

2024-04-18T16:32:40.737712image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-18T16:32:40.963711image/svg+xmlMatplotlib v3.8.3, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime
010.659610106.72832510.0NaN23.16NaNNaN9.0
110.665006106.72836015.0NaN33.11NaNNaN9.0
210.670401106.72839021.08.9116.82NaNNaN9.0
310.675796106.72842427.018.7325.21NaNNaN9.0
410.681191106.72846034.019.0431.96NaNNaN9.0
510.686587106.72849040.0NaN39.84NaNNaN9.0
610.691982106.72853046.0NaN42.31NaNNaN9.0
710.697378106.72856052.0NaN57.06NaNNaN9.0
810.702774106.72860058.0NaN59.59NaNNaN9.0
910.708170106.72863065.0NaN59.56NaNNaN9.0
longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime
69449013.291256106.68362023543.0NaNNaNNaNNaN131.0
69449113.296610106.68352523601.0NaNNaNNaNNaN131.0
69449213.301966106.68343023660.0NaNNaNNaNNaN131.0
69449313.307321106.68334023718.0NaNNaNNaNNaN131.0
69449413.312674106.68324023777.0NaNNaNNaNNaN131.0
69449513.318028106.68316023835.0NaNNaNNaNNaN131.0
69449613.323383106.68306023894.0NaNNaNNaNNaN131.0
69449713.328738106.68297623952.0NaNNaNNaNNaN131.0
69449813.334093106.68288024011.0NaNNaNNaNNaN131.0
69449913.339448106.68278524069.0NaNNaNNaNNaN131.0

Duplicate rows

Most frequently occurring

longitudelatitudealtitudereflectivitytotal_powervelocityspectrum_widthtime# duplicates
4210.65961106.72832510.0NaN17.04NaNNaN143.04
6410.65961106.72832510.0NaN17.07NaNNaN142.04
12610.65961106.72832510.0NaN17.12NaNNaN126.04
1610.65961106.72832510.0NaN16.97NaNNaN159.03
3510.65961106.72832510.0NaN17.03NaNNaN30.03
3710.65961106.72832510.0NaN17.03NaNNaN161.03
4410.65961106.72832510.0NaN17.04NaNNaN154.03
4710.65961106.72832510.0NaN17.05NaNNaN23.03
5010.65961106.72832510.0NaN17.06NaNNaN20.03
5810.65961106.72832510.0NaN17.06NaNNaN146.03